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ECML
2005
Springer
15 years 3 months ago
Error-Sensitive Grading for Model Combination
Abstract. Ensemble learning is a powerful learning approach that combines multiple classifiers to improve prediction accuracy. An important decision while using an ensemble of cla...
Surendra K. Singhi, Huan Liu
BMCBI
2010
208views more  BMCBI 2010»
14 years 10 months ago
A multi-filter enhanced genetic ensemble system for gene selection and sample classification of microarray data
Background: Feature selection techniques are critical to the analysis of high dimensional datasets. This is especially true in gene selection from microarray data which are common...
Pengyi Yang, Bing Bing Zhou, Zili Zhang, Albert Y....
JMLR
2010
146views more  JMLR 2010»
14 years 4 months ago
Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees using Stacking
The success of simple methods for classification shows that is is often not necessary to model complex attribute interactions to obtain good classification accuracy on practical p...
Albert Bifet, Eibe Frank, Geoffrey Holmes, Bernhar...
WWW
2004
ACM
15 years 10 months ago
Query and content suggestion based on latent interest and topic class
To improve the process of user information retrieval, we propose the concept of a latent semantic map (LSM), along with a method of generating this map. The novel aspect of the LS...
Noriaki Kawaeme, Hideaki Suzuki, Osamu Mizuno
AIED
2005
Springer
15 years 3 months ago
Contexts in Educational Topic Maps
This paper explores the idea of using contexts to support more efficient information search in Topic Maps-based digital libraries. The notion of context is d as abstraction of grou...
Christo Dichev, Darina Dicheva